Background: As an important branch of computer vision, visual measurement is a fast
developing cutting-edge technology, which has been widely used in the manufacturing field. In
recent years, the visual measurement of feature size of probes through small IC probes has aroused
Objective: This study aims to take small shaft parts as the research object in order to provide a full
set of novel and reliable technical means for the three-dimension measurement of mechanical parts.
Methods: Firstly, the trinocular vision measurement system based on the curved cantilever mechanism
was designed and constructed. Secondly, the measurement system was used to collect the part
images from different angles, and the images derived from the four categories of segmentation algorithms
such as threshold-based, region-based segmentation algorithm were compared and analyzed.
Lazy Snapping image segmentation algorithm was used to extract the foreground parts of
each image. After comparing and analyzing SfM-based algorithm and Visual Hull-based algorithm,
the SfM-based algorithm was adopted to reconstruct the 3D morphology of the parts. The measurement
of the relevant dimensions was performed.
Results: The results show that Lazy Snapping's human-computer interaction brush function improves
the accuracy and stability of image segmentation of different algorithms, such as threshold
value method, regional method, Grab Cut, and Dense Cut. The SfM-based 3D reconstruction algorithm
is of high robustness and fast speed.
Conclusion: This study provides an effective method for measuring small mechanical parts, which
will shorten the measurement cycle, improve the measurement speed, and reduce the measurement